Microgrid Energy Management Strategy with Battery Energy Storage System and Approximate Dynamic Programming

The growth in distributed renewable power systems provides opportunities to construct more microgrids. With the help of battery energy storage systems (BESS) in the microgrids, the variable and intermittent renewable energy can be smoothed and utilized locally without risking the main electrical grid. Furthermore, the energy costs in microgrids can be reduced significantly with proper control of BESS based on predicted data of renewable power and electricity price. In this paper, we propose an energy management strategy for microgrids with renewable power systems integrated with BESS. A deregulated energy market environment is considered, which allows energy trading from private participates to the main electrical grids. The objective is to maximize the profit gained by selling the excessive renewable energy generated and minimize the cost to meet the load demand in the microgrid, and an approximate dynamic programming algorithm is proposed to solve the issue. The operational cost from battery lifetime consumption is considered, and the rolling horizon approach is utilized for long-term simulation. Both short-term and long-term forecasting are used in the algorithm and updated in every control stage. The algorithm is tested with practical wind power, load demand, and electricity price data.